UPLOAD.md

Publish this release as a Hugging Face dataset

Suggested destination: PureOne/AELYRAITH-III. The repository title and all research content come from the supplied package. This kit prepares a dataset repository containing the manuscript, code, certificates, experiment data, and AI/expert documentation; it does not publish until you run the uploader.

Windows

1. Extract the complete ZIP to a normal folder. Do not run files inside the ZIP.
2. Install Python 3.10 or newer if needed.
3. Double-click UPLOAD_TO_HUGGINGFACE.bat.
4. If no Hugging Face login or HF_TOKEN is available, paste a token at the hidden prompt. It must permit writing the target dataset. The uploader does not save pasted tokens or add them to Git credentials.

The launcher creates a separate .upload-venv, installs the upload dependency, verifies the release, resolves your account's canonical capitalization, and uploads only the manifest-listed release files. The research requirements are not needed for upload. Internet access is needed for dependency installation and publication.

Terminal

The verification and upload plan can be inspected completely offline, using only Python's standard library:

python upload_to_huggingface.py --dry-run

To publish, install the upload client and run:

python -m pip install -r requirements-upload.txt
python upload_to_huggingface.py

The uploader first uses HF_TOKEN or your existing cached Hugging Face login. If neither is available in an interactive terminal, it asks for a token using a hidden prompt. Do not put a token in commands, source files, or the release.

Optional arguments:

python upload_to_huggingface.py --repo-id PureOne/AELYRAITH-III --private
python upload_to_huggingface.py --repo-id YourAccount/YourDataset --dry-run

--private sets the visibility only when creating a new repository. An existing repository keeps its current visibility. --repo-id must belong to the authenticated account or one of its listed organizations. The Hub still checks the token's actual write permission. The default never silently switches publication to another account if a different user is logged in.

Uploads add files and update matching paths. They do not delete unrelated remote files. Re-running the uploader is the recovery path after an interrupted upload. Verify the final dataset page after publication; local verification and mock tests do not establish a successful remote commit.

Manual alternative

Create a dataset repository on Hugging Face, then upload this extracted release's manifest-listed files with their relative folder structure intact. README.md belongs at the repository root. Keep .upload-venv, local tokens, caches, and your private work outside uploaded content. The uploader's --dry-run prints the exact planned paths, including release_manifest.json.

Troubleshooting

Symptom	Action
Checksum or verification failure	Extract a fresh release. After intentional edits, review changes and regenerate the release manifest with the release tooling.
Namespace mismatch	Log in as the intended owner or pass an explicit permitted --repo-id. Canonical account capitalization is preserved.
HTTP 401 / 403	Use a valid token with write access to this dataset and check organization membership where applicable.
HTTP 404	Check the exact namespace and dataset repository type, account access, and token scope.
Temporary network or service failure	Retry the same command after connectivity or service availability returns.

Implementation references

The implementation follows the official Hugging Face documentation, checked 23 October 2026:

• HfApi
• Uploading files and folders
• Authentication

tests/test_upload.py uses a mocked API to test dataset routing, account capitalization, exact file allowlisting, and the offline path. These tests make no Hugging Face requests. Live Windows launcher execution and remote upload are user-side steps.